Kelvin–Helmholtz Instability Waves: A Natural Seeding Mechanism for Orographic Clouds

Natural ice crystal concentrations and snowfall are mainly determined by mesoscale and microscale dynamics such as cloud-top generating cells and Kelvin-Helmholtz (KH) waves over complex terrain. These dynamical mechanisms are especially important between 0° and -15°C where natural ice nucleation mechanisms are inefficient. However, dynamical and microphysical processes associated with natural ice crystal formation, growth, and fallout remain substantial deficiencies in the understanding of orographic precipitation. Here we document the evolution of a KH wave induced seeder cloud and microphysical processes as the seeding ice crystals glaciate a low-level supercooled liquid water cloud. The event occurred at 2045-2230 UTC 18 January 2017 in the Payette Mountains of Idaho during Seeded and Natural Orographic Wintertime clouds: the Idaho Experiment (SNOWIE). In-situ aircraft observations of cloud particles and ice crystal imagery are used in conjunction with an airborne cloud radar and two ground-based dual polarization precipitation radars to show the dynamical and microphysical evolution of KH wave induced snow showers. We found that a series of KH waves originating in the 5.5-6.5 km MSL layer and of 1.5 km horizontal extent were advected northeastward across the Payette Mountains. Reflectivity associated with the KH waves intensified beyond 30 dBZ_e at 5 km MSL as the waves moved across Packer John Mountain, the first large orographic barrier, and then began to lower in echo top height and dissipate as it moved northeast across the Salmon Mountains. Aloft, the KH wave clouds were associated with large positive values of Z_dr near cloud top as plates and columns were generated and about 1 km below the Z_dr maxima we observed maxima in K_dp and reflectivity. As ice crystals fell through the supercooled liquid cloud below and accretion occurred, we observed a decrease in Z_dr towards zero, or slightly negative values, and enhanced reflectivity towards the surface. This study improves our understanding of natural dynamical snowfall mechanisms in complex terrain using an array of active and passive remote sensing and in-situ observations.